This function supports 7 different complex moving averages. These involve multiple steps beyond simple, exponential, etc. In many (but not all) cases results were reconciled against known standards. Included indicators include DEMA (Mulloy double EMA), TEMA (Mulloy triple EMA), EHMA (Hull EMA), WHMA (Hull WMA), TRIX (3-times EMA with rate of change indicator), T3 (Tillson MA), and KMA (Kaufman adaptive MA). The function attempts to remove intervening NaNs before computing specified MA series and then reinsert NaNs into proper place afterwards.
Matthaeus (2020). Complex Moving Average Indicators (https://www.mathworks.com/matlabcentral/fileexchange/52260-complex-moving-average-indicators), MATLAB Central File Exchange. Retrieved .
Thanks, also, it was pointed out the Kaufman moving average uses the movsum function and therefore apparently requires 2016a. Other than the exponential and linear moving averages, movmean (2016a) could be used if one does not have the financial toolbox.
I have used these elaborately smoothed MAs in automated algorithmic trading for fixed income ETFs, with satisfactory results, even including the recent market crash.
thank you very much for your nice work
Thank you for your time
Very user friendly. It is quite useful if you want to try and compare different smoothing techniques.
Expanded to 7 different MA types.